Relay Technologies

Machine learning engineer in logistics

In short

Senior Machine Learning Engineer role at Relay, a fast-growing logistics startup, focused on productionising ML models end-to-end and building out the ML Platform, working onsite in London full-time. The role requires at least 2 years deploying/operating models in production and 4 years building software on high-performing teams, plus comfort working across unfamiliar codebases to ship models into live systems. Salary and benefits are not disclosed in the posting.

About Relay
Relay is fundamentally reshaping how goods move in an online era. Backed by Europe's largest-ever logistics Series A ($35M) led by deep-tech investors Plural, and a recently closed Series B ($95M), Relay is scaling faster than 99% of venture-backed startups. We're assembling the most talent-dense team the logistics industry has ever seen. Relay's mission is to free commerce from friction.
Responsibilities
•Own a critical part of ML: productionising models end-to-end, from training pipeline through live integration to measured business impact.
•Build and mature the ML Platform.
•Evolve the model serving architecture, expand reusable components adoption and set the standards for how Relay ships ML org-wide.
•Strengthen existing models by architecting integration and system testing within training pipelines, automated releases and drift monitoring.
•Launch completely revamped processes side by side with data scientists and measure their real-world impact on the network.
Requirements
•At least two years deploying and operating models in production and four years building software on high-performing teams.
•Comfortable diving into unfamiliar codebases and languages to ship a model into a live system.
•Prefer building the automation that removes manual labour over repeating it.
•Aim with Precision: define problems clearly and measure impact meticulously.
•Play to Win: chase bold bets, tackle the hard stuff, and view constraints as fuel, not friction.
•1% Better Every Day: believe that small, consistent improvements lead to exponential growth; move quickly, deliver results, and learn from every experience.
•All In, All the Time: show up and step up, take ownership from start to finish and do what it takes to deliver when it counts.
•People-Powered Greatness: invest in teammates, give and receive feedback with care and candour, build trust through high standards and shared success.
•Grow the Whole Pie: seek out win-win solutions for merchants, couriers, and customers.
•If these resonate, and you combine strong technical fundamentals with entrepreneurial drive, let's connect.
Conditions
No conditions specified in the posting.

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